The linear equations that arise in interior methods for constrained optimization are sparse
symmetric indefinite, and they become extremely ill-conditioned as the interior method …

Integration of real-time optimization and control with higher level decision-making
(scheduling and planning) is an essential goal for profitable operation in a highly …

We present a scalable approach for the optimization of flip-preventing energies in the
general context of simplicial map**s and specifically for mesh parameterization. Our …

The maximum cardinality and maximum weight matching problems can be solved in Õ (m√
n) time, a bound that has resisted improvement despite decades of research.(Here m and n …

Ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) are
widely used to model control systems in engineering, natural sciences, and economy …

This paper discusses new pivoting factorization methods for solving sparse symmetric
indefinite systems. As opposed to many existing pivoting methods, our Supernode–Bunch …

The ionized gas in Hall-effect plasma accelerators spans a wide range of spatial and
temporal scales, and exhibits diverse physics some of which remain elusive even after …

We present a scalable approach and implementation for solving stochastic optimization
problems on high-performance computers. In this work we revisit the sparse linear algebra …

We present a flexible and scalable method for computing global solutions of high‐
dimensional stochastic dynamic models. Within a time iteration or value function iteration …

A scalable approach computes in operationally-compatible time the energy dispatch under
uncertainty for electrical power grid systems of realistic size with thousands of scenarios …